Childhood white matter disorders: quantitative MR imaging and spectroscopy.

ABSTRACT

PURPOSE: To prospectively investigate whether quantitative magnetic resonance (MR) parameters, including magnetization transfer ratio (MTR), apparent diffusion coefficient (ADC), fractional anisotropy (FA), and MR spectroscopic metabolite concentrations, allow for discrimination between different types of pathologic conditions that underlie signal intensity abnormalities in white matter. MATERIALS AND METHODS: Institutional review board approval and informed consent were obtained. Forty-one patients (19 male, 22 female; mean age, 15.4 years) and 41 control subjects (25 male, 16 female; mean age, 11.3 years) were included. Twelve patients had a hypomyelinating disorder; 14, a demyelinating disorder; five, a disorder characterized by myelin vacuolation; and 10, a disorder characterized by cystic degeneration. Regions of interest were selected within the parietal white matter and were transferred to the corresponding sections of the generated ADC, FA, and MTR maps to extract quantitative measurements. Linear discriminant analysis and univariate analysis of covariance were used for statistical evaluation. RESULTS: Linear discriminant analysis showed that 95% of patients were correctly classified by using total creatine, choline-containing compounds, myo-inositol, MTR, and ADC. In the hypomyelination group, all MR parameters were close to normal, with the exception of elevated total creatine (P = .03) and myo-inositol (P < .001) levels and decreased MTR values (P < .001). In the demyelination group, the levels of choline-containing compounds (P = .02) and myo-inositol (P < .001) were highly elevated. In the myelin vacuolation and cystic degeneration groups, high ADC values (P < .001) and variable decreases in all MR spectroscopic metabolites were seen. MTR was significantly reduced (P < .001) in the cystic degeneration group. CONCLUSION: Quantitative MR techniques can be used to discriminate between different types of white matter disorders and to classify white matter lesions of unknown origin with respect to underlying pathologic conditions.